1. Field of the Invention
The present disclosure relates generally to techniques for signal processing and has been developed with particular but not exclusive attention paid to possible applications in the framework of systems which envisage reduction in the quantity of data required for representing, in a digital format, an image (still picture) or a sequence of images (video sequence).
2. Description of the Related Art
Known to the art are various solutions for efficient compression of digital images. These solutions are usually characterized by a high computational complexity and are not easily integratable in the solutions commonly referred to as System on a Chip (SoC).
The techniques of compression of digital images can be classified in two fundamental groups.
A first group comprises the so-called lossless compression techniques i.e., techniques without loss of quality, which can be used also for processing other types of digital data. The purpose of this type of compression is to remove the statistical redundancy of the data.
To each digital datum there is assigned a variable number of bits, which depends upon the statistical frequency of the particular datum in question.
With reference, by way of example, to the so-called Huffmann compression, to each digital datum there is assigned a variable integer number of bits according to the following rule: short binary codes are assigned to the more frequent data, whereas long binary codes are assigned to less frequent data.
Also known are techniques of arithmetic compression, in which to each digital datum there is assigned a variable and fractional number of bits. The criterion of assignment of the bits is similar to the one used for the Huffmann compression.
Other compression methods are based upon the use of dictionaries. The sequences of the digital data to be compressed are reduced to words of variable length of a dictionary. Corresponding to each word is an appropriate binary code of a fixed or variable length. Belonging in this context is the algorithm for identification of the optimal dictionary due to Lempel and Ziv.
A second group of known compression techniques comprises the lossy compression techniques i.e., techniques with loss of quality.
The purpose of this type of compression is to remove the perceptive redundancy in the data. The image is modified by eliminating what cannot be perceived, or is perceived less, by the human visual system (HVS). The characteristic that is most widely exploited by the visual system amounts to the fact that the sensitivity to low frequencies is higher than the sensitivity to high frequencies. In addition, the perception of the spatial resolution of brightness information is more marked than the perception of chromaticity information.
The representation of the chromaticity information may therefore be less precise, in the sense that the spatial resolution may be lower. The chrominance is, therefore, under-sampled as compared with the brightness. The loss of quality which derives therefrom is practically not perceived by the human eye.
By way of example, for the ITU-R BT.601 standard, the under-sampling ratio between the luminance signal (Y) and the two color differences (CbCr or UV or IQ or DbDr) is 4:2:2. For the well-known MPEG standard the ratio is 4:2:0, where 0 indicates that under-sampling is both vertical and horizontal.
Likewise, the representation of the other sequences may be less precise, in the sense of a coarser quantization, with consequent saving in bits. The loss of perceived quality that derives therefrom is, however, low on account of the lower sensitivity of the visual system to these frequencies.
The splitting into high and low frequencies can be done only after having passed from the spatial domain to the frequency domain by means of the transformation operation. The most widely used transformations are, by way of example, the discrete cosine transform (DCT) and the discrete wavelet transform (DWT).